RQ: What do (self-reported) animal-human relationships tell us about social and political preferences? Are dog-lovers indeed more likely to have conservative and institutionalized values? Is the cat-sphere more associated with progressive and individualist tastes?

Operationalization: How do the users active on Facebook pages for cats and dogs overlap with users active on Facebook pages for politicians?

*Tools:*

1 Netvizz 1 Gephi Findings.

*Protocol:*

1 Search for a national popular "cat page" and "dog page" on Facebook (in the national language) for the following countries: Denmark and Italy. 1 Search for a popular politician for Denmark and Italy. For Denmark: Helle Thorning Schmidt (left) and Pia Kjaersgaard (extreme right) For Italy: Silvio Berlusconni (centre right) and Nichi Vendola (left wing). 1 Extract the data through Netvizz 1 Visualize this in gephi. In gephi, we've appended the files to explore possible overlaps. Findings We extracted and visualized data from Denmark and Italy. In both cases, the spatialization did not indicate that dog lovers were overlapped more with right-wing politicians than cat-lovers.

*Project 2: Eurovision*

RQ: Fans of Eurovision have been accused of voting in regional blocks. But what happens when they indicate their preferences on Facebook? Do post-demographic digital taste data challenge ‘offline’ voting behaviour? And what does this mean - is Eurovision voting revealed as strategic rather than taste-based?

Inspiration:

Controversy and prior research:

Televoting introduced for all countries in 1998, but after a number of critiscism emerged, juries were re-introduced in 2009 (50/50)

Perception of political and geographical voting

Study: ‘Eurovision points-exchange network” - certain countries tend to form "clusters" or "cliques" by frequently voting in the same way - for example Cyprus and Greece.

Possible factors: political alignment (a nation's relationship to the other countries), similar musical tastes, cultures, similar languages, high proportion of expatriates Another study concludes that as of 2006, voting blocs have, on at least two occasions, crucially affected the outcome of the Eurovision Song Contest.

*Tools*:

1 Netvizz 1 Gephi 1 Protocol: 1 Gather Wikipedia-list of the participants (26 countries) from the Eurovision Song Contest Final 2013. 1 Find the Facebook-page for each participant (artists page not song/national Eurovision page) 1 Extract the data (page posts and user posts) from Facebook pages through Netvizz. 1 Visualize in Gephi. 1 Due to time issues and because of data size the German dataset was excluded. 1 The user data from Facebook are not just grouped into different languages but also different kind of “dialects”. Dialects like British English/American English or Netherlands/Belgium/Dutch were merged. 1 Then we merged the languages into 6 groups inspired by supposed voting blocks (Gatherer 2006, found on Wikipedia): Ex-USSR, Balkan Bloc, Nordics+Baltics, Benelux, Southern Europe, UK+Ireland 1 To track the individual database when they were merged in Gephi we made columns based on artists name) 1 (grouping countries) 1 (maybe a modularity-thing for colouring)